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Human and Machine in the New CX
The roles of humans and machines are equally crucial in a hybrid CX.
Not only are they good at different things, but they also complement
each other. The speed and efficiency of computers allow humans
greater freedom to perform other activities that demand their
imagination. Automation is a stepping-stone to take our creativity to
the next level. In that sense, technology must be recognized as the
enabler and accelerator of innovation. It serves the purpose for
which technology was invented in the first place: as the liberator of
human resources.
Before diving deeper into where machines and humans excel, we
need to understand Moravec's paradox. Hans Moravec famously
observed that it is relatively easy to make computers perform well on
intelligence tests but almost impossible to give them the perception
and mobility skills of a one-year-old child.
Reasoning, perceived to be a high-level capability in humans, can
easily be taught to computers since it involves a lifetime of conscious
learning. Because we know how it works, we can simply train
machines with the same logic in a very straightforward process. Due
to their higher computational power, they will learn it faster than we
ever did and use it more reliably.
On the other hand, sensorimotor knowledge—our perception and
response to surroundings—is harder to train into computers. It
appears to be a low-level skill learned during early childhood when

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children effortlessly interact with people and the environment. It is
about intuitively understanding other people's feelings and having
empathy. Nobody knows how a child develops such capabilities as
they mostly come from unconscious learning, built over millions of
years of human evolution. Thus, it is difficult for us to teach what we
do not understand.
AI scientists have been trying to reverse-engineer the unconscious
learning by applying the conscious process. Computers analyze
billions of faces and their unique characteristics to recognize each
one and even predict the underlying emotion. The same goes for
studying voices and languages. Results have been tremendous, but it
takes decades to achieve them. In robotics, there has been limited
success. Robots have managed to replicate our body movement as a
response to external stimuli, but they have failed to reproduce the
gracefulness.
Computers can easily surpass human capabilities that most people
think are our greatest assets—logical thinking and reasoning.
Conversely, what seems natural for humans to learn takes machines
decades and enormous computer processing power to imitate. The
skills that some people often take for granted—for instance, common
sense and empathy—are the ones that differentiate us from
computers. This is the paradox.